The multi-modal features are fused by the language feature \(L\)  and the object features \(O\)  under multiple views. Following [1]}, [2]}, [3]}, we adopt a BERT model [4]} as the language encoder. Given the query expression \(Q\)  with \(k_1\)  words, we embed them into \(d\) -dimensional feature vectors \(L\) , given as:
\(\lbrace l_{s}, l_{1}, \dots , l_{k_1}\rbrace  = \rm {BERT}(Q),\) 
